Understanding Clinician Preferences for Treatment Attributes in Oncology: A Discrete Choice Experiment of Oncologists' and Urologists' Preferences for First-Line Treatment of Locally Advanced/Unresectable Metastatic Urothelial Carcinoma in Five European Countries.

Abstract

Prior discrete choice experiments (DCE) in oncology found that, on average, clinicians rank survival as the most important treatment attribute. We investigate heterogeneity in clinician preferences within the context of first-line treatment for advanced urothelial carcinoma in Spain, France, Italy, Germany, and the UK. The online DCE included 12 treatment choice tasks, each comparing two hypothetical therapy profiles defined by treatment attributes: grade 3/4 treatment-related adverse events (TRAEs), induction and maintenance administration schedules, progression-free survival, and overall survival (OS). We used a random parameters logit model to estimate attribute relative importance (RI) (0-100%) and generate preference shares for four treatment profiles. Results were stratified by country. Preference heterogeneity was evaluated by latent class analysis. In August and September 2022, 498 clinicians (343 oncologists and 155 urologists) completed the DCE. OS had the strongest influence on clinicians' preferences [RI = 62%; range, 51.6% (Germany) to 63.7% (Spain)] followed by frequency of grade 3/4 TRAEs (RI = 27%). Among treatment profiles, the chemotherapy plus immune checkpoint inhibitor maintenance therapy profile had the largest preference share [51%; range, 38% (Italy) to 56% (UK)]. Four latent classes of clinicians were identified (N = 469), with different treatment profile preferences: survival class (30.1%), trade-off class (22.4%), no strong preference class (40.9%), and aggressive treatment class (6.6%). OS was not the most important attribute for 30.0% of clinicians. While average sample results were consistent with those of prior DCEs, this study found heterogeneity in clinician preferences within and across countries, highlighting the diversity in clinician decision making in oncology.